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Self-paced · Entity diagnostics for AI search

The AI-powered Entity Audit

Diagnose and fix how machines understand your site. You will run a complete entity audit on a real website, mine, and come out with a scored diagnosis, a prioritised backlog and a 30/60/90 roadmap you can hand to a client or a content team.

Join the waitlist See the curriculum
  • Lifetime access
  • Certificate of completion
  • Six free browser tools you keep
  • FormatSelf-paced video course
  • Structure7 modules · 27 lessons
  • LevelIntermediate
  • CertificateOn completion
  • AccessLifetime
The problem this course solves

You’ve been told to “do entity SEO” for three years. Nobody told you how to measure it.

So it stays a vibe. You add some schema, you mention a few related concepts, you hope. And when the client asks whether it worked, you have nothing to show them except rankings that move for fifteen other reasons.

Meanwhile the systems deciding what you are relevant for have stopped reading keywords. They read entities, the real-world things your content is about, and the relationships between them.

This course fixes that specific problem. Not the strategy, the diagnosis. A repeatable audit that produces a number you can put in a deck, re-run in ninety days, and show movement on.

And it is demonstrated on a real site with real problems. Not a fictional client, not a tidy example. My own site, live and unedited, including the findings that are embarrassing.

By the end you will be able to answer, with evidence: what does this site look like to a machine, where is that wrong, and what is the cheapest thing to fix first?

What you'll learn

What you’ll take away

Six capabilities that turn entity work from an opinion into a measurement. Each one is practised on a real site, with the dataset bundled so your numbers match the video.

  • Read what a machine thinks your page is about

    Salience, mentions, types and identifiers: the four signals every entity audit reads, and how to spot a page whose subject is not the one you intended.

  • Build an audit corpus you can trust

    Crawl, extract, exclude and sample properly. The step that decides whether every number after it is true, and the four ways it quietly breaks.

  • Score any site on the 5C framework

    Clarity, Coverage, Consistency, Connection and Corroboration, zero to three each, at page and site level, with a fix mapped to every score.

  • Audit the Knowledge Graph properly

    Reconcile your entities to Google’s graph, and catch over-linking: when Google confidently resolves your brand to something else entirely.

  • Find your real competitors, with data

    Current-state versus aspirational sets, and why the gap between how you are classified and how you want to be is the entity problem.

  • Fix what you found, and prove it worked

    Six repeatable fix patterns backed by published research. Then re-run the extraction and show the salience actually moved.

How this course is different

Measured, not asserted

  1. Audited on a real site, including what it got wrong

    Every figure in this course comes from one frozen audit of mlforseo.com and academy.mlforseo.com: 647 pages, 102,752 entity mentions, captured before anything was fixed. The site scored 5 out of 15. You see the findings that are unflattering, because those are the ones that teach.

    Demo site: real, live, unedited

  2. Six tools, free, and yours after the course

    An extractor, a scorecard, a Knowledge Graph reconciler, a consistency checker, a gap matrix and a brief generator. They run in your browser, your API keys never leave the tab, and the second audit takes an afternoon instead of a week.

    You keep: six browser tools

  3. The tactics are research-backed, and the caveats are stated

    Why position beats repetition, why how you name a thing beats how often, why spreading an entity through a page beats concentrating it. Each is traced to published work, with the numbers, and with what the evidence does not support said out loud.

    Grounded in: published research
Curriculum

What's inside

A complete diagnostic path: understand entities, build a corpus you can trust, score it, audit the graph, compare against real competitors, fix what you found, and hand over a roadmap.

Module 0: Start Here2 lessons
  1. 0.1 Course Introduction: What You’ll Build and Who This Is For
    • What the course produces: a scored diagnosis, a backlog, a roadmap and a toolkit
    • Who it is for, and what it assumes you already know (SEO yes, NLP no)
    • The demo site, and why it is real rather than fictional
  2. 0.2 Setup: Your Audit Stack, API Keys and What It Costs
    • Two Google APIs on one key, plus one optional Anthropic key
    • Real cost maths at 1,000, 10,000 and 50,000 pages, and why most audits are free
    • Free-tier limits, quota traps, and the habit of pricing a run before you start it
Module 1: Entity Foundations for Auditors3 lessons
  1. 1.1 Entities, Keywords and Topics: The Mental Model You Actually Need
    • What an entity is (a thing, not a string) and why it is not a keyword
    • The EAV model, applied to auditing rather than theory
    • Three places entities live, and why each one is a different audit
  2. 1.2 How Machines Decide What Your Page Is About
    • The four signals: salience, mentions, type and machine identifier
    • Reading a real API response, field by field
    • The version trap, and four ways extraction quietly breaks
  3. 1.3 The 5C Entity Audit Scorecard
    • Clarity, Coverage, Consistency, Connection, Corroboration: defined and scored
    • The rubric: zero to three, and why precision you cannot defend is worse
    • Scoring the demo site live: it gets 5 out of 15
Module 2: Diagnostics: Extracting the Truth About Your Site5 lessons
  1. 2.1 Building an Audit Corpus You Can Actually Trust
    • The five columns you need, and the one that takes real setup
    • Isolating main content: the selector that decides everything downstream
    • What to exclude, and how to sample a large site honestly
  2. 2.2 Entity Extraction with the Google NLP API
    • The Entity Extractor, step by step, on one page and then a whole corpus
    • What “most common entity” actually returns on a real site
    • Why this course pins API version 1
  3. 2.3 Page Profiles and Prominence Scoring
    • Three filters that turn a hundred thousand mentions into an audit
    • Intended versus detected: the highest-value single diagnostic here
    • Scoring Clarity across the corpus
  4. 2.4 Claude as Your Entity Analyst
    • What the NLP API cannot see, and where an LLM adds something
    • Structured outputs, so the answer is auditable rather than prose
    • Hallucinated entities, and the three checks that catch them
  5. 2.5 Controlling Cost and Runtime
    • The four levers: free tier, batching, caching and model tiering
    • What an audit costs at three site sizes
    • Pricing a run before you spend anything
Module 3: Knowledge Graph Auditing & Entity Mapping5 lessons
  1. 3.1 What Google’s Knowledge Graph Can and Cannot Tell You
    • What a machine identifier is, and what presence in the graph does and does not buy
    • The state of the API in 2026: legacy, read-only, not production-critical
    • Reading resultScore correctly, and why knowledge panels are an outcome not a target
  2. 3.2 Reconciling Your Entities to the Knowledge Graph
    • Running the Reconciler across a real 5,000-entity set
    • Matched, ambiguous, unmatched, and what each verdict means
    • Scoring Connection across your corpus
  3. 3.3 The Unreconciled Entity Report
    • Triaging unmatched entities: genuinely novel, badly named, or noise
    • Choosing one canonical surface form, and making it stick
    • Scoring Consistency
  4. 3.4 Entity Over-Linking: When Google Resolves You to the Wrong Thing
    • Two identifiers on one brand: one generic, one that resolves to nothing at all
    • Detecting it at scale by clustering on identifier
    • Why an over-linked entity is worse than an unlinked one
  5. 3.5 Off-Site Corroboration: Does the Rest of the Web Agree?
    • Wikipedia and Wikidata, and why third-party confirmation moves recognition
    • Asking a model cold, and the distinction between weights and retrieval
    • Scoring Corroboration, and the sentence to get exactly right
Module 4: Competitive Entity Research & Gap Analysis5 lessons
  1. 4.1 Entity Gap Analysis: The Right Way to Compare
    • Current-state versus aspirational competitor sets: the delta is the entity gap
    • Coverage, depth and attribute gaps: three problems, three different fixes
    • Choosing comparables, and why the SERP leader usually is not one
  2. 4.2 Finding Your Real Competitors
    • Discovery by ranking-keyword overlap: how a site is actually classified today
    • The AI-citation set, and why it matches neither of the other lists
    • Live on the demo site, which turns out to be classified as data science, not SEO
  3. 4.3 Topic-Level AI Citation Analysis, and How to Not Fool Yourself
    • Configuring the query so the answer means something
    • The contamination trap, demonstrated on three real queries
    • Sanity-checking AI-visibility data before it reaches a client deck
  4. 4.4 Building the Entity Gap Matrix
    • Running the same pipeline over real competitor content
    • Normalising names across corpora: where most gap analyses break
    • Scoring Coverage, and reading the heat map
  5. 4.5 Prioritising Which Gaps Are Worth Closing
    • Scoring gaps on impact, effort and confidence
    • Quick wins versus structural work
    • The prioritised backlog you actually hand over
Module 5: Remediation: Fixing Entity Representation5 lessons
  1. 5.1 The Six Fix Patterns, and the Research Behind Them
    • Disambiguation, canonical naming, attribute completion, entity-first structure, internal linking, corroboration
    • Why position beats repetition, with the published numbers
    • Each pattern mapped to the dimension it moves and what it costs
  2. 5.2 Fixing Clarity: The Highest-Yield Edits
    • The four placements that matter, in order
    • A worked fix on a real page, re-measured after every round
    • When an edit will not work, and what to do instead
  3. 5.3 AI-Assisted Content Rewriting with Claude
    • Building a rewrite brief from audit data, not from a blank prompt
    • Guardrails: facts, tone and rankings that must survive untouched
    • Proving the fix worked by re-running the extraction
  4. 5.4 Internal Linking on Entity Overlap
    • Finding link opportunities from shared prominent entities
    • Anchor text that reinforces canonical naming
    • Validating against the inlinks report so you do not propose links that exist
  5. 5.5 Structured Data as Entity Definition
    • The five properties that actually carry entity weight
    • The audit check: schema against content against the graph
    • A real contradiction found live on the demo site, and how to repair it
Module 6: Enterprise Scale (coming as a free bonus)1 lesson

Released to all course members at no extra cost. The core 27 lessons are complete without it.

  1. Coming as a free bonus to everyone who buys the course
    • Practical guidance, scripts and tooling for auditing entities at 50,000+ pages
    • BigQuery pipelines, Google Cloud enrichment and incremental runs
Module 7: Roadmap, Reporting & Next Steps2 lessons
  1. 7.1 Your 30/60/90 Entity Remediation Roadmap
    • Sequencing the backlog: what genuinely has to happen first
    • What to re-run, how often, and which numbers to report
    • Built from the demo site’s own audit
  2. 7.2 Everything You Built, and Where to Go Next
    • The corpus, the scorecard, the gap matrix, the backlog and the roadmap
    • The tools and workbooks you keep and re-use on every client
    • How to get your first audit reviewed

Every practical lesson runs on the frozen dataset bundled with the course, so your numbers match the ones spoken on camera, exactly.

Is this course a good fit for you?

This course is for you if…

  • You are an agency, freelance or in-house SEO who has been asked to “do entity SEO” and wants a repeatable method.
  • You work on small to mid-size sites, up to around 50,000 pages.
  • You want a number you can defend in a client meeting, not a list of opinions.
  • You are comfortable with a spreadsheet and willing to paste an API key into a browser tool.
  • You run enterprise SEO. A dedicated practical module on BigQuery, Google Cloud and very large sites is coming as a free bonus. Start here, prove the method on one section first, then scale. The approach is identical at every size; only the infrastructure changes.

It might not be for you if…

  • You want a strategy course on building brand authority and knowledge graphs. That is Beatrice Gamba’s course, and it bundles with this one.
  • You are looking for a deep theoretical treatment of named entity recognition. Introduction to Machine Learning for SEO covers the technique in depth.
  • You want structured data implementation at scale. That is its own course, and it bundles with this one.
  • You are hoping for a guaranteed knowledge panel. Nobody can promise that, and this course says so plainly.
You keep everything

What you'll walk away with

Not notes. Artefacts you re-use on every client, and a toolkit that makes the second audit an afternoon rather than a week.

  • Entity Audit Workbook XLSX

    The scoring sheets, the prioritisation columns and the mapping tables, ready to fill in for your own site.

  • The frozen demo dataset CSV

    The complete audit of a real site, 647 pages and 102,752 entity mentions, captured before anything was fixed, so your numbers match the video exactly.

  • Six browser tools WEB

    Entity Extractor & Salience Profiler, Entity Audit Scorecard, Knowledge Graph Reconciler, Entity Consistency Checker, Entity Gap Matrix and Entity Brief Generator. Free, no account, and your API keys never leave the tab.

  • Your prioritised remediation backlog XLSX

    Every finding scored on impact, effort and confidence, with a named fix pattern and the dimension it moves.

  • A 30/60/90 roadmap XLSX

    Sequenced properly, including the one task that has to start on day one because it is the slowest.

Your instructor

Taught by a practitioner

Lazarina Stoy
LEAD INSTRUCTOR

Lazarina Stoy

Founder of MLforSEO · ML/SEO consultant

Lazarina is a marketing and machine learning consultant, trainer and speaker, and the founder of MLforSEO. She works at the intersection of machine learning and organic search, helping teams apply ML and NLP to problems that actually move the needle rather than to proofs of concept.

This course is built the way she works: on a real site, with every number shown and traceable, and with the unflattering findings left in. The demo site is her own, audited live and unedited, and scoring 5 out of 15 on the day it was recorded.

Focus areas
  • Entity SEO
  • Machine learning for SEO
  • NLP & semantic search
  • Knowledge graphs
  • Marketing automation
Speaker at
  • BrightonSEO
  • SMX
  • MozCon
  • SearchLove
  • Women in Tech SEO
Full profile
Enrolment

Join the waitlist

Get the launch date, the launch price and the first lesson in your inbox.

€150 standard price

Prices exclude VAT. VAT is added for EU individuals.

Questions

Frequently asked questions

Do I need to know anything about entities or NLP before starting?

No. The course assumes you know SEO and assumes you know nothing about entities, natural language processing or knowledge graphs. Everything technical is built up from zero, and every concept is defined before it is used.

Do I need to write code?

No. Everything runs in six browser tools built for the course. There is an optional notebook for the one lesson that uses an LLM, but it is copy-and-run, and that lesson works fine if you just watch.

What will it cost me in API fees?

For most sites, nothing. Google gives you 5,000 free units a month and 100,000 Knowledge Graph lookups a day. The entire audit of the demo site, 647 pages and 102,752 entity mentions, cost zero. A 10,000-page site is around €46, and every tool prices the run before it spends anything.

What does it cost?

The course is €150. Prices exclude VAT; VAT is added for EU individuals. Community members get the usual 30% discount, and it bundles with the related courses. Join the waitlist to hear first when purchasing opens.

When does it open?

Purchasing has not opened yet. Join the waitlist and you will be first to know the moment purchasing opens.

What access do I get?

Lifetime access to the course and every update to it, including the Enterprise Scale bonus module when it is released. More resources are added over time, and course members get them at no extra cost.

Is this suitable for enterprise or very large sites?

Yes, with a sequence. The method is identical at any size; only the infrastructure changes. A dedicated practical module covering BigQuery, Google Cloud and 50,000+ page sites is coming as a free bonus for course members. Learn the approach here and prove it on one section first, then scale it.

How is this different from the Entity SEO & Knowledge Graph Strategies course?

That course is the strategy: building brand entity authority and deploying a knowledge graph. This one is the diagnosis: finding out what is broken and proving it. They fit together. This course tells you what to fix, that one tells you what to build, and they bundle.

Will I get a knowledge panel out of this?

Nobody can promise that, and the course says so directly. Panels are an outcome of entity recognition, not something you can request. What you can measure and move is recognition itself, which is what the scorecard scores.

Is there a certificate?

Yes. A certificate of completion, plus lifetime access to the course and every update to it.

Keep going

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